(2024) 22:331
Stewart et al. BMC Medicine
https://doi.org/10.1186/s12916-024-03555-0

BMC Medicine

REVIEW

Open Access

Chronic kidney disease: detect, diagnose,
disclose—a UK primary care perspectiveof barriers and enablers to effective kidney care
Stuart Stewart1,2,3*, Philip A. Kalra2, Tom Blakeman1, Evangelos Kontopantelis1, Howard Cranmer‑Gordon2 andSmeeta Sinha2,4

Abstract
Chronic kidney disease (CKD) is a global public health problem with major human and economic consequences.
Despite advances in clinical guidelines, classification systems and evidence-based treatments, CKD remains under‑
diagnosed and undertreated and is predicted to be the fifth leading cause of death globally by 2040. This review
aims to identify barriers and enablers to the effective detection, diagnosis, disclosure and management of CKD
since the introduction of the Kidney Disease Outcomes Quality Initiative (KDOQI) classification in 2002, advocating
for a renewed approach in response to updated Kidney Disease: Improving Global Outcomes (KDIGO) 2024 clinicalguidelines. The last two decades of improvements in CKD care in the UK are underpinned by international adoptionof the KDIGO classification system, mixed adoption of evidence-based treatments and research informed clinicalguidelines and policy. Interpretation of evidence within clinical and academic communities has stimulated significant
debate of how best to implement such evidence which has frequently fuelled and frustratingly forestalled progress
in CKD care. Key enablers of effective CKD care include clinical classification systems (KDIGO), evidence-based treat‑ments, electronic health record tools, financially incentivised care, medical education and policy changes. Barriers
to effective CKD care are extensive; key barriers include clinician concerns regarding overdiagnosis, a lack of finan‑cially incentivised care in primary care, complex clinical guidelines, managing CKD in the context of multimorbidity,
bureaucratic burden in primary care, underutilisation of sodium-glucose co-transporter-2 inhibitor (SGLT2i) medica‑
tions, insufficient medical education in CKD, and most recently – a sustained disruption to routine CKD care dur‑
ing and after the COVID-19 pandemic. Future CKD care in UK primary care must be informed by lessons of the lasttwo decades. Making step change, over incremental improvements in CKD care at scale requires a renewed approachthat addresses key barriers to detection, diagnosis, disclosure and management across traditional boundaries
of healthcare, social care, and public health. Improved coding accuracy in primary care, increased use of SGLT2i medi‑
cations, and risk-based care offer promising, cost-effective avenues to improve patient and population-level kidney
health. Financial incentives generally improve achievement of care quality indicators – a review of financial and nonfinancial incentives in CKD care is urgently needed.
Keywords Chronic kidney disease, Primary care, Detection, Screening, Population health, COVID-19, Incentivisedcare, Primary care networks, Integrated care systems*Correspondence:
Stuart Stewart
stuart.stewart@manchester.ac.uk
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
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regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecom‑mons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Stewart et al. BMC Medicine(2024) 22:331

Background
Chronic kidney disease (CKD), characterised by anoften progressive and irreversible loss of kidney function, is a highly prevalent global and national publichealth problem [1]. CKD is classified according to its
cause and into stages according to a patient’s estimatedglomerular filtration rate (eGFR) and albuminuria [2].
Globally, 700 million people (9.1% prevalence) are estimated to have any stage of CKD [3]. In England, adult
CKD (Stages G3-G5) prevalence in primary care was
4.5% as of June 2023, according to CVDPREVENT[4] – a national primary care electronic health record(EHR) auditing tool with coverage of 95% of GP practices. However, prevalence estimates vary depending ondata source, time period and inclusion criteria (Appendix). Whilst several major public health problems haveseen dramatic reductions in global mortality rates since
1990, CKD has not, and is consequently predicted tobe the fifth leading cause of death globally by 2040 [3].
Earlier stages of CKD (G1-G2) are usually asymptomatic, however, as kidney function declines the risk ofacute kidney injury (AKI), cardiovascular disease anddeath rises [2]. Between 2009–2010 in England alone,
CKD was associated with 7,000 extra strokes, 12,000
extra myocardial infarctions, and 45,000 premature
deaths [5]. Although only 1–2% of patients with CKD
will ever progress to kidney failure [2] (KF– G5 witheGFR < 15 ml/min), the cost of managing KF with dialysis and kidney transplants in the National Health Service (NHS) was estimated at £1.34 billion in 2023 [6];dialysis alone is estimated to cost the NHS £34 k per
patient per annum – more than triple the annual valueof a state pension [6]. Patients with CKD also face significant health inequities and health inequalities. For
example, Black and ethnic populations are up to fivetimes more likely to progress to KF requiring kidney
replacement therapy (KRT) yet wait longer for kidneytransplants [7, 8]. Female patients are more likely to bediagnosed with CKD yet male patients are at greaterrisk of progression to KF [7, 8]. Younger patients withCKD are less likely to receive kidney protective andcardiovascular risk-reducing medications (e.g. reninangiotensin system inhibitors (RASi), and statins), yetolder patients are less likely to have their CKD diagnosis recorded [7, 9], and are less likely to receive a kidneytransplant which in turn results in a longer durationof dialysis compounding their already increased cardiovascular risk [7, 8]. Patients of lower socioeconomic
status and patients [10] with significant mental healthdisease are at increased risk of CKD and progression
to later stages of CKD [7]. Patients of lower socioeconomic deprivation are also more likely to be diagnosed late reducing opportunities for risk reduction

Page 2 of 12[7]. A public health problem of this magnitude clearlyrequires a robust and effective detection and monitoring strategy.
The aim of this review is to identify both key barriersand enablers to effective CKD care since the introduction of the Kidney Disease Outcomes Quality Initiative(KDOQI) classification of CKD in 2002. In doing so, we
argue for a renewed approach to managing CKD at boththe patient and population level in response to these barriers and enablers, to a changing healthcare landscape,and updated Kidney Disease: Improving Global Outcomes (KDIGO) 2024 guidelines [2] for managing CKD.
To identify relevant sources and studies for this review,
we conducted a thorough literature search using PubMed, Google Scholar, CINAHL, and grey literaturesources. We used a combination of Medical Subject
Headings (MeSH) terms and free text keywords thatlinked to our main aim and selected these based on areview of high impact papers with subsequent refinement
through iterative searches. The search was limited tostudies published in English or with an English abstract
between January 2000 and May 2024. The search terms
included “chronic kidney disease”, “primary care”, “general practice”, “family medicine”, “detection strategies”,“diagnosis”, “disclosure”, “non-disclosure”, “management”,“screening”, “primary care networks”, “integrated caresystems”, “incentives”, “financial incentives”, “quality andoutcomes framework”, “health inequalities”, “barriers”,
and “enablers”. We reviewed the full text of relevant articles and their reference lists to identify further relevantmaterial.

Detection
The introduction of the KDOQI classification for CKD
in 2002 marked a significant advance in the managementof CKD, providing clinicians with a structured approach
to identifying and categorising kidney disease [11]. The
classification system was later adapted by KDIGO fora global audience [11] and incorporated into the firstguidelines by the National Institute for Health and Care
Excellence (NICE) in 2006 for CKD management. At thesame time, detection, diagnosis, and management wasalso financially incentivised in UK primary care via the
Quality and Outcomes Framework (QOF) from 2006 to2015 [5, 12].
Generally, the medical community embraced the
KDIGO classification system – facilitating a standardised approach to the evaluation and stratification of kidney disease [1]. Clinically, the system helped link diseasestages to specific actions including prescribing, sick day
rules and monitoring, aiding discussions around prognosis and shared decision-making. However, with widespread application, concerns regarding overdiagnosis andStewart et al. BMC Medicine(2024) 22:331

overmedicalisation of natural ageing as a newly defined‘disease’ prompted debate on the utility of the classification system [13]. Critics pointed out the disproportionate prevalence of early-stage CKD compared to KF,
inaccuracies in glomerular filtration rate (GFR) estimation methods like the Modification of Diet in Renal Disease (MDRD) equation, and the characterisation of early
CKD stages as risk factors or pre-disease states, akin topre-diabetes [1]. Further issues included the system’s lackof coherence—where some patients in early stages faced
higher health risks than those in later stages, and thethresholds not reflecting GFR and albuminuria variations
across different ages, sexes, and ethnicities [1]. Theseissues underscored the need for a more nuanced understanding of CKD, recognising the diversity in patient risk
profiles and the variability in kidney function across different populations.
In 2012, the accuracy of GFR estimation improved significantly with the introduction of the Chronic Kidney
Disease Epidemiology Collaboration (CKD-EPI) equation[14] when compared to the MDRD equation. Bolsteredby population-level studies [15], use of the CKD-EPI
equation caused a notable decline in the classification ofindividuals under 70 years old into CKD stages G3-G5—a
7.5% relative decrease, dropping from 15.7% to 14.5%[15]. Conversely, there was a slight rise in the prevalenceof CKD stages G3-G5 among men over 70, from 33.3% to35.5%. Crucially, this research suggested that the CKDEPI equation could potentially lower the overall CKD
prevalence by up to 1.9 million cases and reduce the prevalence of CKD stages G3-G5 by an additional 200,000
cases [15]. Nevertheless, and illustrating the complexityof detecting and defining kidney disease at a populationlevel, recent research examining the application of the2021 CKD-EPI equation (without race modifier for Black
people) in a population of 1.2 m predominantly White
individuals in Stockholm, curiously resulted in 36.2% of
patients with CKD G3a-5 being reclassified into a higher
stage [16]. Therefore, the European Kidney Function
Consortium (EKFC) have developed the EKFC equation[17] to address the age and race limitations inherent to
CKD-EPI whilst having equal performance for Black andnon-Black populations [18].
Despite these advances in addressing overdiagnosis,
the complexity of CKD guidelines and their translation into financial incentives via QOF raised broader
issues related to increasing workloads and administrative pressures on general practitioners (GPs) [19].
Within this framework, aspects of CKD care began to
be viewed as mere bureaucratic formalities [12], eventhough other studies indicated that CKD was still
underdiagnosed [20]. By 2015, incentivised CKD carethrough QOF was discontinued without any national

Page 3 of 12

strategy to assess the impact of this decision on quality of care (QoC) or to ensure the maintenance of existing care standards. This raises the question: how did
removal of CKD care from QOF impact testing anddetection?
Albuminuria testing (QOF indicator CKD004 / CVDPREVENT indicator CVDPCKD004) – critical for the
diagnosis, classification and prognosis of CKD – fell
dramatically from ~ 80% to ~ 40% following withdrawal
from QOF in 2015/16 (Fig. 1). Data from the national
CKD audit (NCKDA) in 2017 raised even more concern
highlighting proteinuria was measured in less than 15%
of non-diabetic patients and only 54% of patients withdiabetes [9] – challenging the assumption that effective CKD care could be absorbed into other financially
incentivised chronic disease care in primary care. Whilst
these findings directly pertain to patients with CKD, it
is reasonable to expect a similar if not worse picture ofproteinuria testing in patients at risk of CKD. Without
measuring proteinuria, our ability to accurately identify
those at greatest risk, especially patients with early stages
of CKD (G1-G2) is significantly undermined.
Research by Wilding et al., measuring changes in several CKD and non-CKD QoC measures following withdrawal from QOF adds more colour to this picture[30]. Specifically, blood pressure control to the targetof < 140/85 mmHg, which had been on an upward trend
from 58.24% in 2007/08 to 68.92% in 2014/15, experienced a decline of 7.78% in 2015/16 to 61.14% (Table 1).
This downturn was not just a matter of fewer CKD
patients reaching the target blood pressure post-QOF
withdrawal but also reflected an increase in the numberof patients who did not have their blood pressure measured at all (noted as CKD002 missed in Table 1). Suchtrends are particularly alarming in light of the concurrent decrease in uACR testing, increasing the potential
for accelerated progression of kidney disease and missed
opportunities for early intervention. Morales et al. [31]highlighted through a controlled interrupted time series
analysis a worsening of performance in 12 of 16 QoC
indicators by one year and 10 of 16 QoC indicators by
three years across several chronic diseases after withdrawal of QOF in Scottish primary care, compared withEngland [31]. Whilst the authors did not measure theimpact on CKD QoC indicators, withdrawal did impact
complex care processes (diabetes, mental health disease)and therefore CKD care (also a complex care process)may well have been adversely impacted post-QOF [31].
When considering these findings through the lens of
behavioural psychology, work from Lepper et al. [32] in
1973, highlights removal of extrinsic rewards underminesinternal motivation and can result in not only loss of
positive behaviours (detecting and diagnosing CKD) but

Stewart et al. BMC Medicine(2024) 22:331

Page 4 of 12

Fig. 1 National CKD urine ACR % achievement by year. Created from NHS Digital QOF, Indicators No Longer in QOF (INLIQ) [21–28],
and CVDPREVENT [29] source data. Note: Indicator CKD004 was known as CKD006 from 2009/10 to 2012/13

Table 1 Quality and outcomes framework CKD indicator(CKD002 and CKD004) performance over time in primary care in
England. Date sources – Wilding et al. [30], NHS Digital QOF andINLIQ data [21–25, 28], and CVDPREVENT [29] dataYear

QOF indicators
CKD002
achieved

CKD002
not achieved

CKD002
missedCKD004aachieved

2007/08

58.24%

31.22%

8.68%-

2008/0959.73%

29.83%

8.12%-

2009/1060.68%

29.66%

7.15%

85.3%

2010/1162.43%

28.05%

6.79%

82.2%

2011/1263.40%

26.76%

6.96%

82.2%

2012/1363.60%

25.36%

7.83%

81.8%

2013/1470.72%

19.45%

7.27%

80.9%

2014/1568.92%

19.86%

8.37%

80.2%

2015/16

61.14%

24.18%

10.72%

40.2%

2016/1761.87%

25.26%

10.11%

38.3%

Key: CKD002: The percentage of patients on the CKD register in whom the lastblood pressure reading (in the preceding 15 months) is 140/85 mm/Hg or less;
CKD004: The percentage of patients on the CKD register whose notes have arecord of a urine ACR or PCR test in the preceding 15 months; aCKD004 was
CKD006 from 2009/10 to 2012/13

also worsening of performance in general (managing preexisting CKD).
Policymakers and leaders must therefore consider,prior to implementation, how population-level changes
to care (such as withdrawal of financially incentivisedcare) could impact patient and health system outcomes
including whether health inequalities will be createdor widened. In the interests of transparency and due
diligence, these analyses should be published. Decision
analysis – popular in business, economics and publichealth, used to forecast the consequences of different
COVID-19 lockdown exit strategies in the UK [33], could
help policymakers and leaders forecast unforeseen consequences of withdrawal of financial incentives prior to
implementation.
The predictive power of proteinuria in kidney diseaseprogression risk is well-established and beyond dispute[2]. The question is not whether to measure and monitor
proteinuria but how to effectively implement its measurement. The integration of such tests within financiallydriven incentives via QOF within primary care proved to
be unacceptable. Thus, it raises the question of whether apopulation health strategy, leveraging the organisational
structures of Primary Care Networks (PCNs) – introduced in 2019 in England and tasked with providing
integrated community-based clinical and social care,might offer a more efficacious approach. Addressing
major public health challenges necessitates populationlevel strategies, which are foundational to the operationsof Integrated Care Systems (ICSs) and PCNs; these networks have already demonstrated their potential in effectively managing major public health problems, as seen in
their critical role in the national COVID-19 vaccination
program [34].

Stewart et al. BMC Medicine(2024) 22:331

Considering the role of screening in the detection of
kidney disease—the NHS Screening Committee does not
currently endorse population screening, citing concerns
over cost-effectiveness and clinical efficacy [35]. This
position stems in part from the absence of treatments
proven to significantly slow the progression of CKD [35].
However, it’s crucial to acknowledge the aetiologicalcomplexity of CKD as a condition. Unlike more homogeneous diseases like aortic aneurysms (where screening
is endorsed), CKD encompasses a wide variety of underlying causes that contribute to kidney function decline,
making it difficult to neatly apply NHS screening criteria. Notably, longitudinal research in UK primary carefrom 2013 to 2017 revealed 44% of adults aged 60 + had
undiagnosed CKD, even after excluding terminally ill
and older adults unable to consent [36]. Such data underscores the high yield and potential benefits of targeted
screening in high-risk groups – where CKD screening
is recommended [2]. Given the prevalence of CKD and
its human and economic consequences [5, 6], identifying and screening those at greatest risk is imperative. The
emergence of new treatments, such as sodium-glucose
co-transporter 2 inhibitors (SGLT2i), which not only aid
in glycaemic control but also significantly reduce risk ofcardiovascular events, death, and kidney disease progression risk [37], should therefore prompt a re-evaluation of
the current stance on CKD screening [38].

Diagnosis
Central to the debate around overdiagnosis is the question – what is the utility of a diagnosis of CKD? Diagnosis encompasses not only the identification of CKD but
also the subsequent recording and coding (applicationof a diagnostic clinical code; e.g., SNOMED CT, ICD10, retired Read codes) [39] of the diagnosis within primary care EHR systems and disclosure of the diagnosis
with patients. Here we consider diagnosis and coding
before disclosure. Coding CKD in the EHR is associatedwith numerous benefits for both clinicians and patients.
In fact, coding a diagnosis of CKD is one of the single
most cost-effective tools at a clinician’s disposal owing to
the myriad of protective downstream effects of applying
diagnostic clinical codes [9]—automated patient recall
for routine CKD reviews; automated recommendations
to perform kidney function testing in line with guidelines;
cross-disease EHR alerts to encourage kidney function
testing in at-risk groups; automated and timely prescribing warnings to promote kidney protective medications
in line with clinical observations (e.g., blood pressure)and discourage harmful medication prescribing (NSAIDs[40]); as well as vaccination eligibility alerts. Interestingly, not only does neglecting to code a diagnosis notafford these positive benefits, it is also associated with

Page 5 of 12

major adverse health outcomes for patients, revealed in
the NCKDA; patients with uncoded CKD stages G3-G5
experience up to 500% higher mortality risk, comparedto patients whose CKD is appropriately coded, whenmatching for age, sex, disease stage and comorbidities[41]. Furthermore, patients with uncoded CKD are also
at greater risk (increasing risk as eGFR decreases) of
unplanned hospital admissions and AKI [41]. Althoughassociations between uncoded CKD and the presence ofother significant health conditions, such as dementia andadvanced cancer [9] may theoretically amplify this risk,
the magnitude of risk increase is nevertheless substantial. With this in mind, the NCKDA findings highlights aconcerning issue: not only are there clear inconsistencies
across England and Wales in how CKD is identified inprimary care but there is a wide disparity in how a CKD
diagnosis is recorded (coded) for patients with biochemical evidence of CKD (reduced eGFR and raised uACR),
with rates varying from 0 to 80% [9].
Considered from another angle, the importance ofbeing able to effectively identify CKD at both the individual and population level came into sharp focus as
CKD emerged as a major risk factor for death fromacute COVID-19 infection in adults [42, 43]. Moreover,patients with CKD require ‘special attention’ owing toincreased mortality risk [43] (Table 2), tailored shielding
advice [44, 45], and reduced vaccine efficacy [46]. Here,the power of a diagnostic clinical code emerges – used
as a key instrument by NHS England and GP Practices(as well as specialist nephrology services) for identifying
patients with CKD for shielding advice [45], care planning [47, 48], and vaccination priority [49]. How then,were patients with uncoded CKD (Table 2: 30.1% of CKD
G3-G5 [50]) expected to receive such lifesaving care andwhat impact did this failure to code a diagnosis of CKD
have on patient outcomes? Although unknown, given
uncoded CKD is associated with increased all-cause
mortality risk [41], it is reasonable to assume uncoded
CKD may also be associated with increased COVID-19
mortality risk. With such compelling and clinically plausible associations between uncoded CKD and adverse
health outcomes [41], why do so many patients with biochemical evidence of CKD [9] not have a diagnostic clinical code? Research shows an extensive list of barriers toeffective CKD care which influence diagnosis and coding (summarised in Table 3). Clinician concern regarding
overmedicalisation is an often-cited barrier to making adiagnosis, however, a less apparent but vitally importantbarrier (and in itself an enabler) to address is clinicians’
lack of awareness of the associated benefits of coding adiagnosis and the harm associated with not. In fact, coding a diagnosis of CKD is an equity imperative, especiallyin the context of future pandemic preparedness.

Stewart et al. BMC Medicine(2024) 22:331

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Table 2 Mapping of CKD stages G3-G5 from NCKDA data [50] to hazard ratios regarding risk of death from COVID-19 fromOpenSAFELY data [42]National CKD Audit data [50] from 8.24 m adults inprimary care in England and Wales

OpenSAFELY data [42] from 17 m adults in primary care in
Englandn with biochemical CKD
at round 1 of NCKDA% codedfor CKD% uncoded
for CKD

Fully adjusted hazard ratios (95% CIs)
Primary analysis

Early censoringat 6/4/2020

Adjusted for ethnicity
using multiple
imputationCKD Stage 3a

160,100

60.8

39.2

1.33 (1.28–1.40)

1.49 (1.36–1.63)

1.33 (1.27–1.39)

CKD Stage 3b78,855

82.5

17.5

CKD Stage 4

17,22489.7

10.3

2.52 (2.33–2.72)

2.98 (2.57–3.43)

2.50 (2.31–2.70)

CKD Stage 5

3,254

90.3

9.7

All CKD 3–5

259,433

69.9

30.1

Table 3 Summary of primary care practitioner’s (PCP’s) reported barriers to effective CKD care in primary care considered as apotential barrier to detection, diagnosis, disclosure and management [52–58]
Potential barrier toa
Specific barrier
System Factors

Detection Diagnosis Disclosure Management

Limited visit time to care for complex patients

✓

✓

✓

✓

Lack of standardised quality of care metrics

✓

✓

✓

✓

✓

✓

Lack of comprehensive clinical information (EHR) systems✓✓

Lack of integration of clinical decision support tools in the EHR

✓

✓
✓

✓

✓

✓

✓

Long waiting lists for specialist nephrology services
Poor reimbursement/funding for delivering optimal CKD care
Primary Care Factors PCP’s limited recognition or knowledge of CKD
PCP’s lack of awareness of CKD guidelines or useful protocols for CKD
care

Patient Factors

a

✓

✓

✓

✓

✓

✓

✓

✓

✓

✓

PCP’s difficulty in assimilating/implementing complex CKD guidelines✓✓

PCP’s experience that CKD risk factors are difficult to manage

✓

✓

✓
✓

PCP’s beliefs that they are unable to improve CKD

✓

✓

✓

✓

PCP’s perceptions that proteinuria testing has no impact on manage‑
ment

✓

✓

✓

✓

Difficulty in integrating proteinuria testing into primary care workflows

✓

✓

✓

✓

PCP’s concerns regarding overdiagnosis

✓

✓

✓

✓

PCPs not wanting to worry patients about a diagnosis

✓

✓

✓

✓

Managing patient and family expectations: Uncertainty of prognosis;
Fostering acceptance of kidney disease severity risk

✓

✓

✓

✓

Complexity of conservative medical management: PCP’s ability to provide best-practice renal care in primary care; integrating multidisciplinary
healthcare professionals✓

Negotiating roles and responsibilities when jointly managing patientswith specialists✓

Patients’ limited understanding of CKD and its implications

✓

✓

✓

✓

Patients unable to afford recommended CKD care✓

Patients intolerant of CKD medication side effects✓

Insufficient clinical support tools/resources to support self-manage‑
ment✓

our assimilation of whether a reported barrier is generally a potential barrier to detection, diagnosis, disclosure and/or management; not nessarily considered insource references

Stewart et al. BMC Medicine(2024) 22:331

At a population level, clinicians can easily detect
patients with uncoded CKD using two main methods:
within their own practice using population health searchtools built into EHR systems where patients are identified
by biochemical findings (eGFR and uACR) and clinicalcodes, and in England – with the CVDPREVENT tool
[29] which quickly quantifies the number of uncodedcases of CKD whilst summarising by health inequality
measures, at a practice, PCN, ICS, regional and national
level. These diagnostic tools are crucial components ofa workflow that is integrated with Quality Improvement
initiatives, a strategy proven to significantly enhance
diagnostic clinical coding for CKD at the populationlevel [51] which sets the stage for diagnosing and coding
uncoded cases of CKD at the patient level.

Disclosure
The debate around disclosure or more precisely, non-disclosure of CKD with patients is complex and nuanced [59,60]. Research documents several barriers to clinician disclosure of CKD as a diagnosis (Table 3). However, there
is also a wealth of evidence showing these barriers canbe addressed. One concern among clinicians is the fearof distressing patients regarding a diagnosis that might
not noticeably affect their health [56]. Yet, interventional
research that embraced a need for ‘minimally disruptive
medicine’ [61], demonstrates tailored communicationand support through community-based CKD management can enhance health-related quality of life and maintain blood pressure control, without a detrimental effecton patient anxiety [62]. Such community-based interventions align with the establishment of a wider PCN workforce, blending clinical care with social prescribing andbroader health and wellbeing initiatives [63]. With a clear
move towards a risk-based approach for CKD detection
and management, the use of new predictive tools such as
the Kidney Failure Risk Equation (KFRE) – incorporated
in to NICE CKD 2021 guidelines [64], enable clinicians
to predict a patient’s risk of requiring KRT, which can aid
in shared-decision making and potentially lessen bothclinician and patient anxiety. Interestingly, patients withand without CKD who inaccurately report their multiple
health conditions have an increased risk of death, after
adjusting for age, sex and race [65]. This suggests that
accurately understanding one’s own health status has aprotective effect further necessitating disclosure of CKD.
Moreover, patients express a desire to be informed ofearly stages of CKD to facilitate shared decision-making
and self-management [66]. On the other hand, clinicians
may hesitate to disclose a diagnosis of CKD to somepatients with major comorbidities such as metastatic
cancer or cognitive impairment. However, disclosing
the diagnosis to patients’ next of kin opens up avenues

Page 7 of 12

for holistic supportive care. It is crucial to note, coding
a diagnosis in the EHR does not equal disclosure. Yet,
doing so makes a patient’s kidney impairment visible
for all healthcare practitioners and triggers helpful automated alerts within the EHR [8]. The negative implications of non-disclosure, whilst not immediately apparent,
also extend to clinicians – a contributing factor for a GP
practice being rated inadequate by Care Quality Commissioners and losing its contract to practise [67].
Guidelines increasingly reflect a shift away from terminology that imply disease and deficit towards preserving health, seen in the NICE AKI quality standards [68],alongside integration of CKD into models of maintaining cardiovascular health [69]. Patient-centred researchsuggests that framing discussions about CKD in termsof maintaining kidney health can encourage patients totake a more active role in their health and by doing so,patients may be more inclined to adopt lifestyle choices
and behaviours that preserve kidney function [70].

Management
To emphasise the advantages of early detection anddiagnosis – it is vital to highlight the availability of evidence-based interventions that are proven to reduce
mortality, cardiovascular, and kidney disease progression
risks. First, RASi (angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers) reduce progression to kidney failure (KF) in patients with albuminuria[2]. Second, SGLT2i are capable of reducing mortality
and cardiovascular event risk, as well as reducing therate of kidney disease progression [2, 71]. Third, lipid
lowering therapy with statins reduces mortality and cardiovascular event risk [2, 72]. Importantly, RASi, SGLT2i,
non-steroidal mineralocorticoid receptor antagonists andlipid lowering therapies are underutilised in primary caresettings in several countries [71, 73, 74]. Fourth, specifictherapies tailored to patient’s individual needs and causeof CKD offers additional benefits, e.g., SGLT-2 inhibitors
in patients with diabetes, immunosuppressive therapy inpatients with lupus nephritis [75]. Whilst these interventions principally benefit individual patients, certain strategies can enhance CKD care at the population level. For
example, a collaboration between primary and secondary
care physicians to deliver virtual renal clinics have beenshown to reduce waiting times for specialist advice (64to 6 days), reduce outpatient appointments, and improve
clinician confidence in managing CKD [76]. Addressing
mortality risk, two key levers are available for primarycare clinicians to pull immediately – a strategic focus on
increasing the uptake of SGLT2i for eligible patients [2]and coding a diagnosis of CKD in all patients with biochemical evidence of CKD [41].

Stewart et al. BMC Medicine(2024) 22:331

A risk-based approach is central to identifying thosepatients in greatest clinical need that would benefit from
specialist nephrology input, whilst balancing the concerns of overdiagnosis; the KFRE helps to strike this balance. Whilst the KFRE does not predict life-time risk of
KRT, doesn’t consider the competing risk of death, and iscurrently undergoing external validation to ensure it performs fairly in different ethnicities [77] it has been validated and calibrated for a broad UK population prior to
implementation and can predict with high accuracy thoseat greatest risk of KRT [55]. Other risk prediction tools
such as KDPredict combine risk of kidney failure withthe competing risk of death [78] – an important addition
to kidney failure risk prediction which can further support shared decision making and referrals to nephrology.
As the KFRE is dependent on eGFR and uACR measurements, primary care clinicians must address the generally poor utilisation of uACR to achieve this risk-based
approach. Research has shown that some primary careclinicians lack awareness that measuring uACR can positively impact CKD management [53] therefore medical
education is an essential component to influence change.
This education must extend to the wider PCN workforce
including physician associates and nurse practitioners
who receive substantially less training than physicians.
When used, the KFRE is helpful in shaping shared decision-making, communicating prognosis, and triggeringreferral to nephrology for patients with 5-year risk of 5%
or more [64, 79].
The complexity and breadth of CKD clinical guidelines hinder effective CKD care highlighting the need forpractical solutions. Digital clinical decision tools offer aremedy by distilling extensive guidelines into actionableclinical recommendations. For instance, acknowledging
that CKD invariably needs to be placed in the context of
supporting people living with multiple long-term conditions, the GP evidence tool used in England [80, 81] condenses key intervention evidence into concise high-yield
information on intervention benefits and harms. Similarly, in Canada, the CKD Pathway serves as a streamlined flowchart and guide for diagnosing and managing
patients with CKD [82]. Another challenge is the isolated
approach of guidelines that focus on single diseases,
neglecting the fact that CKD is often diagnosed in thecontext of multiple long-term conditions. The CardioRenal-Metabolic (CaReMe) UK partnership exemplifies a
unified approach to this problem by integrating cardiovascular, renal and metabolic disease management [69].
An innovative outcome of this collaboration is a revised
type 2 diabetes (T2D) guideline which balances a traditional ‘glycaemia-based approach’ with a cardiorenal risk
approach, prioritising SGLT2i to reduce cardiovascularand renal event risk [69] – a strategy now reflected in the

Page 8 of 12

latest NICE T2D clinical guidelines [83]. While incorporating elements of CKD care within the broader scopeof maintaining vascular health through initiatives like
CaReMe has advantages, it is crucial to recognise that itshould complement, not replace holistic CKD care that is
tailored to individual patient needs.
Financial incentives have demonstrated a mixed but
generally positive impact in the management of chronic
diseases through care quality indicators and a reduction in health inequalities [84, 85]. Conversely, removing financial incentives in primary care has been linked
to a loss of such positive impacts [30, 31, 86]. In the UK,
the removal of financial incentives for managing patientswith CKD is compounded by the asymmetrical andinadequate weighting of primary care funding in areasof high socioeconomic deprivation [87], where CKD is
more prevalent [8]. Whilst there is a dearth of evidencecomparing financial incentive models in CKD care inprimary care to support policy changes and populationlevel interventions, British Columbia—Canada is trying a
new, evidence-informed approach to managing complex
longitudinal care, and in doing so, addressing key systemlevel barriers (Table 3) to CKD care. For example, a new
reimbursement model in primary care financially incentivises primary care clinicians for providing longitudinalcare to patients with complex care needs which supports
clinicians in spending more time with patients in greatest
need [88].

Conclusions
Reflecting on 22 years of evidence since the KDOQI classification of CKD through to the latest KDIGO CKD
2024 guidelines [2] underlines the complex interplay ofdetection, diagnosis, and disclosure in the managementof CKD within primary care and across health systems.
The evidence presented illuminates continuous anditerative attempts to navigate tensions between different
stakeholders, objectives, outcomes and evidence whichhave often hindered as well as helped. Yet, these attempts
have sought to find balance; balance between the utilityof classification systems in their ability to structure andconstrain our efforts in delivering effective CKD care[89]; balance between delivering individualised patientcare and care for populations; balance between optimal CKD care and health system sustainability; balance
between the unique skillsets of generalists and specialists;
and balance between the tenets of primary care, specialist care, social care and public health. Achieving balance
is not only essential for improving patient care and outcomes, but ensuring healthcare professionals remain
engaged in delivering effective CKD care in ways that are
sustainable for professionals and health systems alike.

Stewart et al. BMC Medicine(2024) 22:331

Page 9 of 12

Table 4 Estimates of CKD prevalence in England and Wales across different sources over time
SourceTime period

Sample population

Age

Male (%)

Female (%)

All (%)

Estimated CKD
stage G3-G5 in
Englanda

NEOERICA [90]1998–2003

130,226

18 +

5.8

10.6

8.5

3,640,321 [5]HSE [91]

2003

7,844

16 +

-

-

7.7

-

CPRD [30]

2006–2007

484,152

18 +

2.73

3.78

3.25

-

QOF [5]2009–2010

-

18 +

-

-

4.3

1,817,871 [5]HSE [91]

2009–2010

6,053

16 +

-

-

7.0

2,710,575 [5]QICKD [92]2011

930,997

0+

3.48

7.34

5.4

2,817,104 [5]-OxRen [36]2013–2017

861

60 +

-

-

13.9

National CKD Audit [9, 41]

2015–2016

5,200,000

18 +

-

-

5.5–5.8~ 1,500,000

HSE [91]

2016

3,766

16 +

-

-

7.3

-

CPRD [30]

2016–2017

400,213

18 +

5.19

7.26

6.24

-

QOF / PHE [93]2018–2019

-

18 +

-

-

4.1

1,935,056

QOF / PHE [93]2021–2022

-

18 +

-

-

4.0

1,962,990

CVDPREVENT coded [4]June 2023

49,352,336

18 +

3.38

4.47

3.93

1,937,683

CVDPREVENT uncoded [94]June 2023

49,352,336

18 +

0.54

0.68

0.61

301,851

CVDPREVENT combined
coded and uncoded [4, 94]

June 2023

49,352,336

18 +

3.92

5.16

4.54

2,239,534

Key: where no values are reported, this is due to a lack of reporting in the source dataaestimates from source data

Looking ahead, a renewed approach to addressing CKD
care across traditional boundaries of healthcare, social
care and public health is needed. This approach must be
informed by the lessons of the last two decades, prioritiseinterventions that tackle barriers to detection, diagnosis
and disclosure, all whilst responding to the evolving landscape of healthcare delivery. Forecasting and measuring
the impact of such interventions and strategies will bepivotal in demonstrating clinical and cost-effectiveness.
Beyond making incremental improvements to previous
suboptimal care, this approach should seek to deliver
personalised care on a scale previously unimagined. ICSs
and PCNs and the professionals within them hold thepotential to achieving such goals. Achieving these goals
requires a collective effort from patients, policymakers,
clinicians, and researchers to define and usher in a newera of CKD care.

Appendix
Table 4Abbreviations
AKI	Acute kidney injury
CaReMe	Cardio Renal Metabolic
CINAHL	Cumulative index to nursing and allied health literature
CKD	Chronic kidney disease
CKD-EPI	Chronic Kidney Disease Epidemiology Collaboration
CVDPREVENT	Cardiovascular disease prevent

CPRD	Clinical Practice Research Datalink
eGFR	Estimated glomerular filtration ratio
EHR	Electronic health record
KF	Kidney failure
GP	General PractitionerHIV	Human immunodeficiency virus
ICBs	Integrated care board/s
ICSs	Integrated care system/s
KDIGO	Kidney Disease: Improving Global OutcomesKDOQI	Kidney Disease Outcomes Quality Initiative
KFRE	Kidney failure risk equation
MDRD	Modification of Diet in Renal DiseaseNCA	Northern Care Alliance
NCKDA	National chronic kidney disease audit
NHS	National Health Service
NICE	National Institute of health and Care Excellence
NSAID	Non-steroidal anti-inflammatory drug
PCN	Primary care network/s
QOF	Quality and outcomes framework
QoC	Quality of care
RASi	Renin-angiotensin system inhibitors
KRT	Kidney replacement therapy
T2D	Type 2 diabetes
SGLT2i	Sodium-glucose co-transporter-2 inhibitoruACR​	Urine albumin creatinine ratio
Acknowledgements
No acknowledgements.
Authors’ contributions
SSt: conceptualisation; data curation; visualisation; writing – original draft
preparation; writing – review and editing; PK: writing – review and editing;supervision; TB: writing – review and editing; supervision; EK: writing – review
and editing; supervision; HCG: writing – review and editing; SSi: writing –review and editing; supervision. All authors read and approved the final
manuscript.

Stewart et al. BMC Medicine(2024) 22:331

Authors’ information
SSt is a General Practitioner and researcher undertaking a PhD in Epidemiol‑ogy examining changes in CKD care and outcomes over time using national
data through the Clinical Practice Research Datalink (CPRD). PK is a professorof nephrology at Salford Royal, Northern Care Alliance (NCA) NHS Founda‑tion Trust and University of Manchester, Director at the NCA department ofResearch & Innovation. TB is a GP and Clinical Senior Lecturer at The Universityof Manchester, Centre for Primary Care & Health Services Research, with a
special interest in kidney health research. EK is a professor of data science andhealth services research at The University of Manchester, Centre for Primary
Care & Health Services Research. HCG is a patient with chronic kidney disease
and is a member of a patient and public involvement group to support theco-development of research with SSi, PK and SSt in NIHR funded research; SSi
is the NHS England National Clinical Director for Renal Medicine, a consultant
nephrologist at Salford Royal, Northern Care Alliance (NCA) and is a professorof nephrology at the Manchester Academic Health Sciences Centre, Universityof Manchester.
Authors’ X Handles
EK: @dataevan.
Funding
SSt receives funding from Kidney Research UK; award number
AHPF_001_20220705. The funder did not have any role in the creation of thisarticle.
Availability of data and materials
Data is provided within the manuscript or supplementary information files.

Page 10 of 12

2.
3.

4.

5.
6.
7.
8.
9.
10.

11.

Declarations

12.

Ethics approval and consent to participate
Not applicable.

13.

Consent for publication
Not applicable.

14.

Competing interests
SSt receives funding from Kidney Research UK; award number
AHPF_001_20220705. SSi received honoraria from AZ, Boehringer, Menar‑ini, Novartis, GSK, CSL Vifor and Bayer. PK received grant funding from CSL
Vifor and Astellas, consulting fees from Astra Zeneca, Vifor, Unicyte and UCB,
honoraria from Astra Zeneca, Pfizer, Pharmacosmos, Medice, GSK, Bayer and
CSL Vifor. EK – None to declare. TB – No financial conflicts of interest; NHS
England Think Kidneys Programme Board Member (2014–17); Royal Collegeof General Practitioners’ AKI Clinical Champion (2017–20); NHSE Renal Services
Transformation Programme Post-AKI care Lead (2021–23); Specialist Commit‑
tee Member for NICE AKI Quality Standard (QS76) (2022–23); Kidney Disease
Improving Global Outcomes (KDIGO) AKI Guideline Work Group (2023-Todate). HCG none to declare.
Author details
1
The University of Manchester, Centre for Primary Care & Health Services
Research, Manchester, UK. 2 Donal O’Donoghue Renal Research Centre,
Northern Care Alliance NHS Foundation Trust, Manchester, UK. 3 Rochdale Care
Organisation, Northern Care Alliance NHS Foundation Trust, Manchester, UK.
4
Manchester Academic Health Science Centre, The University of Manchester,Manchester, UK.

15.
16.

17.

18.
19.
20.

Received: 1 June 2024 Accepted: 5 August 2024
21.
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